Extreme value analysis of wave climate in Chesapeake Bay

A thirty-seven year wave hindcast (1979-2015) in Chesapeake bay using NCEP's Climate Forecast System Reanalysis (CFSR) wind is presented. The long-term significant wave heights are generated by the third-generation nearshore wave model SWAN, which is validated using the wave height measurements at buoy stations in the bay. The simulated wave heights are analyzed to characterize their temporal and spatial variabilities as well as long-term changing trends by using an Empirical Orthogonal Function (EOF) analysis and an empirical cumulative distribution function approach. Seasonal variability as well as extreme storm effects on significant wave heights are revealed in the first mode of principle component. Then, an extreme value analysis based on generalized extreme value and generalized Pareto distribution functions is applied to evaluate design wave heights with different return periods. The effects of key parameters including threshold value, time span and data length on the design wave heights are extensively studied. Through the comparisons of different distribution functions evaluated by Bayesian Information Criterion and Akaike Information Criterion, it is found that Gamma distribution function and generalized extreme value analysis provide the best fit for annual and monthly data, while generalized Pareto distribution function gives the best fit when peak-over-threshold analysis is conducted.